Effectiveness of Chamfer Texture Loss. In the presence of imperfect poses and high-frequency details in textures, we show in Tab. REF  that our proposed pixel- and feature-level Chamfer texture losses are highly effective compared to existing losses. In particular, pixel-to-pixel L1 loss tends to give blurry reconstructions. Feature-based losses, perceptual loss [1]} and contextual loss [2]}, are generally more robust to misalignment, but they are usually not discriminative enough to reflect the appearance details between two images. Although the contextual loss is designed to address the misalignment issue for image-to-image translation, it only considers feature distances while ignoring their positions in the image.
